Apparatus and method for large field-of-view measurements of geometric distortion and spatial uniformity of signals acquired in imaging systems

ABSTRACT

An apparatus and method for imaging quality assessment of an imaging system employs an aggregate phantom and a processor for imaging analysis. The aggregate phantom includes a plurality of self-contained sections configured to be moved independently and re-assembled in the imaging system. Each section includes fiducial features of known relative location. The processor: quantitatively determines location of the fiducial features within an image of the aggregate phantom; compares the determined location within the image to the known relative location of the fiducial features to produce a distortion field; and distinguishes between actual geometric distortion of the imaging system and rigid-body transformations of sections of the aggregate phantom, in the distortion field. For extended fields-of-view, the aggregate phantom may be repositioned, and sets of images combined to determine a distortion field of the extended image. A method employing virtual features for measuring spatial uniformity of an acquired signal, is also provided.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. patent application Ser. No.16/721,048, filed on Dec. 19, 2019, which claims priority to U.S. patentapplication Ser. No. 15/589,557, filed on May 8, 2017, which claimspriority to U.S. Provisional Application No. 62/356,332, filed on Jun.29, 2016. The contents of the foregoing applications are herebyincorporated herein by reference in their entirety.

FIELD OF THE INVENTION

This invention relates, in general, to an apparatus and method forevaluating performance of an imaging system or scanner and, moreparticularly, to an aggregate phantom and analysis method especiallyuseful for large field-of-view measurements in an MRI scanner or otherimaging system.

BACKGROUND ART

Recent developments in the field of radiation therapy have enabledincreasingly precise control of the applied radiation dose. Doseprofiles can fall off very rapidly over distances on the millimeterscale, enabling therapy to be applied close to critical anatomy, whilesubjecting such anatomy to acceptably low radiation exposure. Thisincreased control of the applied dose has motivated increased attentionto the digital imaging systems used to plan the therapy.

Magnetic resonance imaging (MM) is of increasing interest for radiationtherapy planning because it provides superior soft-tissue contrast toCT, enabling better visualization of pathological tissue relative to thehealthy tissue. MRI, however, suffers from lower quantitative accuracyrelative to CT, particularly in the area of geometric distortions. MRimages have distortions that commonly reach several millimeters inmagnitude.

It is possible to measure such distortions using phantoms and imageanalysis. Such techniques have been applied for many years over volumespertinent to neurological scanning, using a Magphan® quantitativeimaging phantom available from the Phantom Laboratory, Incorporated,located in Salem, N.Y. This phantom includes a large number of fiducialobjects (markers or features) that can be located accurately within animage. Plastic spheres of 1-1.5 cm diameter are typically used as thefiducial objects. The relative location of each fiducial object is knownahead of time based on the design of the phantom, and that knownlocation can be compared to the measured location of each fiducialobject in the image. The difference characterizes the distortionthroughout the volume covered by the fiducial objects.

A major challenge, however, is to perform such measurements over large,3D fields of view that are pertinent to body imaging. A phantom largeenough to cover such fields of view can weigh more than 100 pounds (45kilograms), making it difficult to use in a clinical environment. Thehigh weight is driven by the large volume and the need to fill thephantom with liquid in order to generate an MR signal. Classically, thisis done with a very large phantom which can weigh over 100 pounds.

Others have addressed this challenge by applying a mathematical resultthat enables characterization of the geometric distortion throughout avolume based only on measurements of the distortion on a surface thatsurrounds the volume. This solution has several practical shortcomings:

-   -   1. The phantom is still heavy, presenting a challenge for safe        handling by a wide range of clinical personnel.    -   2. The high weight of the phantom makes it difficult to add        additional measurements beyond distortion, as this would further        increase the weight. The currently available product performs        only distortion measurements.    -   3. The measurements are performed with a pre-determined set of        MRI pulse sequences, and do not always characterize the        distortion that pertains to a specific pulse sequence used        during clinical imaging.

An alternative solution, not previously applied to this problem, is toconstruct the phantom of multiple, self-contained sections that aremoved separately and reassembled on the imaging system patient table.Once reassembled, the sections are meant to function collectively as asingle large phantom assembly or aggregate phantom.

A concern with this approach, however, is achieving the tight toleranceson the geometry of the assembled phantom sections. An accuracy of 0.5millimeters or better is desired for the distortion measurements. It isextremely difficult to control the precision of the location of eachphantom section relative to the other sections with such accuracy whileenabling it to be re-assembled easily by the user. Further complicatingthe task, is the severe restriction on acceptable materials that can beused inside an MRI scanner to avoid safety issues and imaging artifacts.

Accordingly, there is a need for a practical method and apparatus tomeasure, with precision, geometric distortion of an imaging system, overlarge, 3D fields of view.

Maintaining acceptable levels of distortion in an MR scanner relies onproperly controlling many conditions. It is critical to have a robustsystem of quality control for key imaging performance characteristics inorder to detect significant deviations before they affect clinicaloperations.

Although an aggregate phantom may cover a large field-of-view, it maystill not cover the entire field-of-view that may be of interest forsome applications. Accordingly, there is a need for a technique to coveran entire field-of-view with a phantom that encompasses less than theentire field of view.

One common measurement performed on imaging systems is the spatialuniformity of the signal acquired. Uniformity can be a useful indicatorfor common failure mechanisms in subsystems such as an RF coil. Theuniformity is usually measured by creating a large, uniform region of aphantom and studying the variation of the signal in an image of theuniform region. There are two common configurations used for thismeasurement:

-   -   1. A uniform region that covers only a single or a very small        number (2 or 3) slices, and is oriented only in one direction,        i.e., the measurement will support only slices oriented in one        direction. In some imaging systems such as MRI, slices can be        acquired in any orientation and so such a limitation is        undesirable.    -   2. A phantom, often large, consisting of a uniform fill with no        other features inside.

There are also phantoms made of multiple sections, each with nothinginside except background fill. An assumption made in using such phantomsis that the fill in each section is the same as in all the othersections. This assumption can be unsettling, particularly for MRI, wherethe fill is fluid and the chemical properties can change over time.

Accordingly, there is also a need for an apparatus and method formeasuring spatial uniformity of a signal acquired by an imaging systemwhile compensating for signal differences attributable to differentcompositions or properties of different sections of a phantom.

BRIEF SUMMARY OF THE INVENTION

To address and overcome the above-noted problems, an aggregate phantomor phantom assembly composed of multiple, individual, self-containedsections or compartments that fit together and each have fiducialfeatures at known relative locations, is provided by the presentinvention.

To measure and compensate for any imprecision in the locationand/orientation of the individual sections relative to one another inthe aggregate phantom, an analysis method is provided, preferablyemploying spheres as fiducial features, to determine the orientation ofthe phantom sections in an image. The data from the sample sections isthen combined, preferably using mathematical analysis, into a singledata set that covers a field-of-view. The analysis method provides a mapof the geometric distortion over the entire 3D volume covered by themultitude of individual sections. The aggregate phantom and analysismethod is particularly useful in measuring geometric distortion.

A novel aspect of the analysis method is the determination, from thefiducial features in the individual sections, of residual imperfectionsin the location and/or orientation of each individual section of theaggregate phantom. Such imperfections may be due to limitations in theprecision of the manufacturing or assembling process. The analysismethod of the present invention facilitates resolution of positionalimperfections in the placement of each individual section of theaggregate phantom, and distinguishes between a physical displacementcomponent attributable to such positional imperfections and actualgeometric distortion of the imaging system.

The analysis method can determine these residual imperfections in anumber of different ways.

One approach is to use a small number (such as 3-10) of “landmarkfeatures” or fiducials to identify each individual section, and from thepositions of the landmark features determine the position andorientation of the individuals sections within the aggregate phantom.

An alternative approach is to include in the calculation of thedistortion field, mathematic terms that apply a translation and arotation in three dimensions, and perform an optimization calculation tobest fit the distortions to a set of basis functions appropriate todescribing the distortion field. Some examples include polynomials,spherical harmonics, and trigonometric functions. It will be appreciatedby those skilled in the art that many possible basis function sets mightbe appropriate. The basis set is modified to include and separatelyidentify functions that apply positional offsets due to independenttranslation and rotation of each individual section.

The analysis method of the present invention facilitates use of anaggregate phantom with multiple, separate, self-contained compartmentsor sections, which may be readily, independently transported andre-assembled within the imaging system, and facilitates integration ofthe imaging data into one large data set to measure, with precision,distortions over a field-of-view which encompasses all of the individualcompartments or sections.

The aggregate phantom of the present invention may cover a largefield-of-view, but may not cover the entire field-of-view that may ofinterest for certain applications. In such circumstances, an analysistechnique may be employed that takes, as inputs, sets of images with theaggregate phantom (or a standard phantom) scanned in different locationswithin the imaging system or scanner. In this method, the aggregatephantom is scanned in an initial position and then moved to one or morenew locations such that the volume covered by the image scans cover theentire field-of-view of interest. The multiple image scans may or maynot overlap. The analysis method then combines these data sets usingmethods similar to those applied for combining the different individualsections in the aggregate phantom to provide measurements covering theentire field-of-view that is covered by the multiple scans.

According to the present invention, apparatus for image qualityassessment of an imaging system, may comprise: an aggregate phantomhaving a plurality of self-contained sections configured to be movedindependently and re-assembled in the imaging system, each sectionincluding fiducial features of known relative location, and a processorfor image analysis configured for: quantitatively determining locationof the fiducial features within an image, produced by the imagingsystem, of the aggregate phantom; comparing the determined locationwithin the image to the known relative location of the fiducial featuresto produce a distortion field; and distinguishing between actualgeometric distortion of the imaging system and rigid-bodytransformations of sections of the aggregate phantom, in the distortionfield.

The distinguishing may comprise: identifying and quantifying thedisplacement components attributable to the rigid-body transformationsof individual sections of the aggregate phantom, and determining thegeometric distortion over a field of view covered by more than onesection of the phantom by removing the displacement components from thedistortion field.

The distinguishing may further comprise: fitting a smooth function tothe distortion field, augmenting or modifying the smooth functions toinclude functions that characterize the rigid-body transformations ofindividual sections of the aggregate phantom to produce an augmented ormodified set, and determining coefficients of the augmented or modifiedset.

The fitting may comprise: using, as a basis, at least one ofpolynomials, spherical harmonics, or another set of distinct functionswith spatial characteristics for fitting slowly-varying functions, anddetermining a least-squares fitting of the coefficients.

Each self-contained section may advantageously include a uniformbackground liquid.

The fiducial features may advantageously comprise spheres.

The plurality of self-contained sections may comprise at least twoadjacent, adjoining, contiguous, stacked or side-by-side sections.

In another aspect, at least one of the plurality of self-containedsections may include at least one additional feature for measuring anadditional characteristic of the imaging system.

The additional characteristic may comprise at least one of: slicethickness, spatial resolution, spatial uniformity of a signal acquiredby the imaging system, ghosting, and signal-to-noise ratio. Ghosting iswhen dim copies of some portion of an image appear elsewhere in theimage.

When the additional characteristic comprises spatial uniformity of asignal acquired by the imaging system, a plurality of virtual featuresis attributed to each section of the aggregate phantom at specifiedlocations containing only background liquid, and the processor mayfurther: measure average values within regions of the imagecorresponding to the virtual features; interpolate between the averagevalues to determine spatial uniformity of a signal acquired by theimaging system, throughout a measurement volume of the phantom; andcompensate for any differences in composition between the sections ofthe aggregate phantom in determining the spatial uniformity of theacquired signal throughout the measurement volume. The virtual featuresare theoretical constructs rather than true physical structures.

The imaging system may comprise a magnetic resonance imaging system, orother imaging system.

In another aspect, a method for image quality assessment of an imagingsystem, may comprise: locating, within the imaging system, an aggregatephantom having multiple self-contained sections, each section includingfiducial features of known relative location; creating an image of theaggregate phantom with the imaging system; and, with a processor:quantitatively determining location of the fiducial features within theimage, comparing the determined location within the image to the knownrelative location of the fiducial features to produce a distortionfield, and distinguishing between actual geometric distortion of theimaging system and rigid-body transformations of the sections of theaggregate phantom, in the distortion field.

According to this method, the distinguishing may comprise, with theprocessor: identifying and quantifying a displacement componentattributable to rigid-body transformations of the sections of theaggregate phantom; and determining geometric distortion over a field ofview covered by more than one section of the phantom by removing thedisplacement component from the distortion field.

The method may further comprise: determining the known location of thefiducial features by measurements on an alternative imaging system orfrom design and construction of the sections of the aggregate phantom.

In a further aspect, the method may further comprise: including, in atleast one of the self-contained sections, at least one additionalfeature for measuring an additional characteristic of the imagingsystem.

When the additional characteristic comprises spatial uniformity of asignal acquired by the imaging system, a plurality of virtual featuresis attributed to each section of the aggregate phantom at specifiedlocations containing only background liquid, and the processor mayfurther: measure average values within regions of the imagecorresponding to the virtual features; interpolate between the averagevalues to determine spatial uniformity of a signal acquired by theimaging system, throughout a measurement volume of the phantom; andcompensate for any differences in composition between the sections ofthe aggregate phantom in determining the spatial uniformity throughoutthe measurement volume.

In yet another aspect, a method for performing distortion measurementsof an imaging system with a phantom over a field of view larger than animaging volume of the phantom, may comprise: acquiring a set of images,with the imaging system, of the phantom positioned at multiple locationswithin the field of view; combining the set of images to form anextended image; determining a distortion field of the extended image;and distinguishing between actual geometric distortion of the imagingsystem and rigid-body transformations attributable to repositioning ofthe phantom, in the distortion field.

According to this method, the phantom may comprise an aggregate phantomhaving multiple self-contained sections, each section including fiducialfeatures of known relative location, and the distinguishing may includedistinguishing between the actual geometric distortion of the imagingsystem and rigid-body transformations of the sections of the aggregatephantom, in the distortion field.

In a further aspect, a method for measuring spatial uniformity of asignal acquired by an imaging system, may comprise: locating a phantomwithin the imaging system; attributing virtual features to regions atknown locations throughout a measurement volume of the phantom, eachregion containing only background liquid; imaging the phantom with theimaging system; and, with a processor: measuring average signals withinthe regions, and interpolating between the average signals to determinespatial uniformity of a signal acquired by the imaging system,throughout a measurement volume of the phantom.

In this method, the phantom may comprise an aggregate phantom having aplurality of self-contained sections, the locating may compriseseparately transporting and re-assembling the sections within theimaging system, the attributing may comprise attributing the virtualfeatures to regions in each section, and the processor may furthercompensate for any differences in composition between the sections ofthe aggregate phantom in determining the signal uniformity throughoutthe measurement volume.

Each virtual feature may have a spherical or other shape.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

Details of preferred embodiments of the invention will be presented inconjunction with the accompanying drawings, in which:

FIG. 1 is a sectional view from the side of a first embodiment of anaggregate phantom of the present invention;

FIG. 2 is a view illustrating the two separate, self-contained sectionsof the aggregate phantom of FIG. 1 ;

FIG. 3A is a view of the two sections assembled as an aggregate phantom;

FIG. 3B is a sectional view from the front of the aggregate phantom;

FIG. 3C depicts the interior structure of the two sections of theaggregate phantom including location of fiducial features of theaggregate phantom;

FIG. 4 depicts a second embodiment of an aggregate phantom of thepresent invention;

FIG. 5 illustrates the three, self-contained sections of the aggregatephantom of FIG. 4 ;

FIG. 6A is a sectional view from the side of the aggregate phantom ofFIGS. 4 and 5 ;

FIG. 6B is a sectional view from an end of the aggregate phantom of FIG.6A;

FIG. 7 depicts the inclusion of additional features in a phantom sectionto measure additional characteristics of an imaging system;

FIG. 8 depicts one section of an aggregate phantom;

FIG. 9 depicts the attribution of virtual features in the one section ofFIG. 8 ;

FIG. 10 depicts the attribution of virtual features in an aggregatephantom;

FIG. 11 depicts an online analysis service to implement the methods ofthis invention; and

FIGS. 12A-D depicts the creation of an extended image by repositioningof an aggregate phantom.

DETAILED DESCRIPTION

This invention involves an analysis that distinguishes rigid-bodytransformations of phantom sections from an actual geometric distortionof the imaging system being studied. An analysis that can make such adistinction enables a phantom to be constructed out of multiple sectionswhich, in turn, enables each section to be light enough to be movedsafely in clinical environments.

Each section of an aggregate phantom can be “off” by a translation and arotation (collectively referred to herein as a “rigid-bodytransformation”) relative to other sections. Any errors could beinterpreted as a geometric distortion instead of a phantom tolerance ordisplacement. Therefore, in order to use such a phantom, a technique isprovided to distinguish real geometric distortions from rigid-bodytransformations of each section of the aggregate phantom.

This distinction is made by taking advantage of the nature of geometricdistortions. Geometric distortions are relatively slowly-varyingfunctions, and can be fit to a variety of mathematical functions such aslow-order polynomials. Typically, polynomials of order three to ten ineach dimension are adequate to characterize the distortion accurately.

A rigid-body transformation has a distinctive spatial characteristic.All of the fiducial markers within one section move in tandem to thesame rigid-body transformation. Fiducials in a different section move toa different rigid-body transformation. Since geometric distortionsultimately originate from deviations of the magnetic fields in thescanner, no physically-realizable distortion would have such a spatialcharacteristic.

This distinctiveness gives rise to the analysis method of the presentinvention that identifies and quantifies the rigid-body transformations.After first measuring the locations of each of the fiducial markers, afit is performed to a function that includes not only the functions usedto fit the true geometric distortion, but is also augmented by functionsthat characterize separate rigid-body transformations of each section ofthe phantom. The original basis set may be further modified to identifya subset of the basis functions that describe only translations androtations of the individual sections. The coefficients of this fit canbe used to separate out the rigid-body transformations of phantomsections from true geometric distortion of the image.

Once such a distinction is made, an aggregate phantom can be built outof several, light-weight sections, enabling large field-of-view coveragewith a multi-section phantom that can be transported, and handled,section by section, and then re-assembled on site. A related benefit ofhigh commercial significance is that such a phantom can also have otherfeatures in it that perform additional measurements of the scanner orimaging system. Other important measurements such as slice thickness,spatial resolution, spatial uniformity of a signal acquired by theimaging system, signal-to-noise ratio, etc. may thus be performed withthe same aggregate phantom used to measure geometric distortion.

An aggregate phantom 10, comprised of two separate, independentlytransportable, self-contained sections 12, 14, is illustrated in FIGS.1, 2 and 3A-C. FIG. 2 shows the multiple sections prior to theirreassembly as the single aggregate phantom illustrated in FIG. 3A.

The multiple sections of the aggregate phantom may be positionedadjacent, or adjoining, or contiguous, or stacked, or in a side-by-siderelationship.

The individual sections are of relatively low weight, e.g. each under 12kilograms, and can be easily transported separately, and have featuresthat help position them accurately relative to one another.

Each self-contained section may be filled with a uniform backgroundfluid or liquid 16, e.g., a copper sulfate and water solution thatproduces a bright signal in an MR image. The sections may also contain alarge number (approximately 200-300) fiducial features or markers in theform of 1-cm plastic (e.g., polycarbonate) spheres 18, at known relativelocations. These spheres appear dark in an MR image. This specificchoice of sphere size enables a highly-precise determination of theposition of the spheres within the image, to approximately 20% of thedimension of the voxels in the image. Spheres of other sizes and/ormaterials compatible with the imaging modality may be employed.

The fiducial features may take other shapes and forms. In addition, eachsection may also contain other features used to perform differentmeasurements pertinent to the imaging scanner or system, as more fullydescribed hereinafter.

Some fiducial markers 20 within the phantom sections are distinctive inappearance from the others, and are used to provide a preliminaryposition and orientation determination of the section of the phantom.These landmark fiducial markers may, for example, comprise 1.5-cmdiameter spheres, while the rest of the fiducial features are 1.0-cmdiameter spheres.

The spheres or other fiducial features may be supported in each sectionby any appropriate support structure. Examples of such supportstructures 22, 24 are illustrated in FIG. 3C, and may include, forexample, a series of polycarbonate plates and posts to maintain thefiducial features in fixed known relative locations within the section.

Each section of the aggregate phantom may have a housing 21, cast orotherwise formed, for example, from a clear urethane material. Thehousing fully encloses the support structure, fiducial features, otherfeatures, and background fill or fluid of the section, rendering eachsection self-contained.

The shape, size, construction, location and material of the housings mayvary from that illustrated, as may the configuration, construction andmaterial of the support structures.

By combining multiple, independently transportable, self-containedphantom sections into one aggregate phantom, a large field-of-view maybe covered, while avoiding excess weight. The sections of the aggregatephantom of the present invention can be individually transported andhandled, and then can be reassembled on the patient table of the imagingsystem. Once reassembled, the sections are meant to functioncollectively as a single large aggregate phantom.

FIGS. 4, 5, 6A and 6B illustrate a second embodiment of an aggregatephantom 30 of the current invention. Aggregate phantom 30 includes threesections: a top section 32, a middle section 34 and a bottom section 36.Again, each section is independently transportable and self-contained.The three sections may be initially aligned using landmark fiducialfeatures 38 to form the aggregate phantom 30 illustrated in FIG. 4 . Asshown in the sectional views of FIGS. 6A-B, each section of aggregatephantom 30, in addition to the landmark fiducial features, may include alarge number of other fiducial features 40, at known relative locations,for use in measuring geometric distortion of the imaging system.

The fiducial features and landmark fiducial features of aggregatephantom 30 may be similar to, or different than, the correspondingfeatures of aggregate phantom 10. Again, each section of aggregatephantom 30 may be filled with a uniform background fluid 42 thatprovides a bright signal in an MR image.

The two section aggregate phantom 10 may, for example, measure geometricdistortion over a 35×27×21 cm volume. The three section aggregatephantom 30 may cover a larger field-of-view than the two section version10, while still avoiding the problem of excess weight. The higher thenumber of sections, the greater the modularity and configurationalvariations of the aggregate phantom.

The number, size, shape, and relative positioning of the sections of theaggregate phantom may vary from that shown. Although particularlybeneficial for determining geometric distortion and othercharacteristics of an MRI imaging system, the aggregate phantom of thepresent invention may be used with other imaging equipment andmodalities.

Similarly, the distribution, location, number, shape, material and sizeof the fiducial features may vary from that illustrated, provided thatthe fiducial features are sufficient to measure geometric distortion ofthe imaging system over the desired field-of-view.

Accuracy of 0.5 millimeters, or better, is desired for geometricdistortion measurements of the imaging system. This imposes tighttolerances on the geometry of the assembled phantom sections.

It is extremely difficult to control the precision of the location ofeach phantom section relative to the other sections with such accuracywhile enabling the aggregate phantom to be re-assembled easily by theuser. Further complicating the task, is the severe restriction onmaterials acceptable for use inside an MRI scanner to avoid safetyissues and imaging artifacts.

Each section of the aggregate phantom can be “off”, i.e., displaced, bya translation and a rotation (collectively referred to herein as a“rigid-body transformation”) relative to other sections. Any suchpositioning errors might be interpreted as a geometric distortioninstead of a section displacement. Therefore, a technique is provided todistinguish real geometric distortions of the imaging system fromrigid-body transformations of each section of the aggregate phantom.

Once such a distinction is made, aggregate phantoms can be build out ofseveral sections, enabling large field-of-view coverage with a phantomthat is still readily handled. A related benefit of high commercialimportance is that such an aggregate phantom can also have otherfeatures in it that perform additional measurements of the imagingsystem. Such measurements may include slice thickness, spatialresolution, spatial uniformity of the signal acquired by the imagingsystem, signal-to-noise ratio, etc. FIG. 7 schematically illustrates theinclusion of such additional features 44, 46, 48 among fiducial features40 of a section of an aggregate phantom.

In a single-section phantom, the geometric distortion field may bedetermined by measuring the location of each fiducial marker in theimage of the phantom relative to its known position within the phantom.A smooth function may be fit to the distortion field using commonmathematical functions as a basis, such as polynomials, spherical,harmonics or any set of distinct functions with spatial characteristicsappropriate for fitting slowly-varying functions.

The coefficients of the fit can be determined in a large variety ofways. A least-squares fit of the coefficients is currently preferred.However, different and/or more complicated fitting functions could alsobe used that would employ different fitting techniques.

For the multi-section aggregate phantoms of the present invention, theset of functions used to fit the distortion field is augmented withfunctions that are nonzero only within one section of the phantom. Forexample, to characterize a rigid-body transformation of one section, sixsuch basis functions are required: three translational basis functionsand three rotational basis functions. For N sections, there are 3N basisfunctions attributable to rigid-body transformations of the sections.

In the presently preferred embodiment, a least-squares fit is performedusing the augmented set of functions as the basis set. A displacementcomponent that arises from the 3N rigid-body basis functions, is removedfrom the total measured distortion, and the remainder comprises the realgeometric distortion of the imaging system.

One common measurement performed on imaging systems is the spatialuniformity of the signal acquired by the imaging system. Uniformity canbe a useful indicator for common failure mechanisms in subsystems likethe RF coil element.

Applicants have developed a new method for performing uniformitymeasurements that does not require a perfectly uniform region of thephantom, and compensates for signal differences attributable todifferent compositions or properties of different sections of a phantom.According to this method, the background is sampled in multiple (e.g.,hundreds) of regions throughout a three-dimensional volume of thephantom section. These regions are referred to herein as “virtualfeatures” and are identified ahead of time from the design of thephantom as regions where there is known to be nothing but backgroundfill.

FIG. 8 shows a representative section 50 of an aggregate phantom. InFIG. 9 , the attributed locations of spherical virtual features 52 areshown superimposed on section 50. As illustrated in FIG. 10 , suchvirtual features are advantageously attributed to all sections of theaggregate phantom.

The shape, size, distribution, number, and location of the “virtualfeatures” may, of course, vary from that illustrated, provided that eachvirtual feature corresponds to a region of the section containing onlybackground fill or fluid.

Since the typical signal variations are slowly varying, as long as thesample regions corresponding to the virtual features are taken withsufficiently close spacing to one another, an accurate interpolation canbe performed between the samples, and the uniformity characterizedeverywhere.

The advantages of this technique include:

-   -   1. The entire region of the uniformity measurement does not need        to be dedicated to the uniformity measurement; it can,        advantageously, contain other features.    -   2. Measurements can be made over entire volumes rather than just        a small number of slices in a single slice orientation.

The use of virtual features to measure spatial uniformity of the signalacquired by an imaging system can be applied to a single section or amulti-section phantom. Using a multi-section aggregate phantomintroduces a non-ideality that has to be addressed, namely, that eachsection can, in principle, have slightly different properties that wouldcause a difference in signal relative to the other sections. Thisdifference could be incorrectly interpreted as a signal non-uniformity.

The method to overcome this potential aberration is related to themethods described above for measuring geometric distortion withmulti-section aggregate phantoms. A fit of the signal variation isperformed to a function that includes not only continuous,“well-behaved” functions like polynomials, but also includes degrees offreedom associated with each section, such that each section is alloweda signal offset that is uniform within that section.

A fit is then performed to the functions, and the components of thedistortion associated with uniform offsets within each section areattributed to differences in the phantom sections rather than truevariations of the underlying signal. The present invention, thus,accommodates not only rigid-body transformations but also differences inthe composition or other properties of the sections of an aggregatephantom.

Pursuant to the present invention, to measure spatial uniformity of asignal acquired by an imaging system, a plurality of virtual features isattributed to each section of the aggregate phantom at specifiedlocations containing only background liquid, and a processor may:measure average values within regions of the image corresponding to thevirtual features; interpolate between the average values to determinespatial uniformity of a signal acquired by the imaging system,throughout a measurement volume of the phantom; and compensate for anydifferences in composition between the sections of the aggregate phantomin determining the spatial uniformity of the acquired signal throughoutthe measurement volume.

Once the signal has been characterized continuously throughout the fieldof view of the phantom, any desired measurement can be performed. Someexamples are the mean, normalized standard deviation, spread, etc.

The various calculations and compensations of the analysis methods ofthe present invention can be implemented with a programmable processor,either associated with the imaging system or separate therefrom. Theanalysis may also be provided via an online service such as Image OwlTotal QA™ hosted by Image Owl Inc. of Greenwich, N.Y. Such onlineanalysis service is illustrated in FIG. 11 , wherein aggregate phantom30 re-assembled on patient table 54 is imaged by MR imaging system 56,and the image is analyzed, in accordance with the methods of the presentinvention, by a remote processor 58, and the results, e.g., in the formof a report, are conveyed to a computer, tablet, phone or the like 57,via the internet 59.

The present invention also provides a method for performing geometricdistortion measurements, of an imaging system, with a phantom, over afield-of-view larger than an imaging volume of the phantom, even that ofan aggregate phantom.

In this method, multiple sets of images are taken of the phantom 60positioned at multiple locations within the extended field-of-view, bythe imaging system. Such repositioning is illustrated in FIGS. 12A, 12Band 12C. This set of images may then be combined to form an extendedimage as figuratively illustrated in FIG. 12D. A 3D distortion field ofthe extended image is then determined, and actual geometric distortionof the imaging system is distinguished from rigid-body transformationsattributable to repositioning of the phantom, in the distortion field,in a manner similar to that described above for rigid-bodytransformations attributable to section displacements.

An analysis technique may be employed that takes, as inputs, sets ofimages with the aggregate phantom (or a standard phantom) scanned indifferent locations within the imaging system or scanner. In thismethod, the aggregate phantom is scanned in an initial position and thenmoved to one or more new locations such that the volume covered by theimage scans cover the entire field-of-view of interest. The multipleimage scans may or may not overlap. The analysis method then combinesthese data sets using methods similar to those applied for combining thedifferent individual sections in the aggregate phantom to providemeasurements covering the entire field-of-view that is covered by themultiple scans.

Similarly, by moving the phantom relative to the pertinent components ofthe imaging system, multiple image acquisitions of the phantom can alsobe combined to provide an extended uniformity measurement in a mannersimilar to that described above for measuring geometric distortion byrepositioning a phantom.

The present invention thus enables precise measurement of geometricdistortion over a wide, large or extended field-of-view and precisemeasurement of spatial uniformity of a signal acquired by the imagingsystem by using (and optionally repositioning) an aggregate phantomwithin the imaging system. The aggregate phantom avoids the weightconstraints of the prior art while facilitating multiple differentmeasurements with the same aggregate phantom.

The modular design of the aggregate phantom, enables the light-weightphantom sections to be readily handled by a single person withoutspecial equipment. The related analysis methods automatically compensatefor displacements or varying properties of the phantom sections, orphantom repositioning.

The apparatus and methods of the present invention meet the specificQuality Assurance needs of MR imagers used for MR guided surgery, andradiotherapy planning and guidance where measurement of largefield-of-views are required for torso sizes encountered in clinicalpractice. The present invention facilitates a robust system of qualitycontrol for key imaging performance characteristics in order to detectsignificant deviations before they affect clinical operations andpatient outcomes.

The invention claimed is:
 1. A method for measuring spatial uniformityof a signal acquired by an imaging system, comprising: locating aphantom within the imaging system; attributing virtual features toregions at known locations throughout a measurement volume of thephantom, each region containing only background liquid; imaging thephantom with the imaging system; and with a processor: measuring averagesignals within the regions, and interpolating between the averagesignals to determine spatial uniformity of a signal acquired by theimaging system, throughout a measurement volume of the phantom.
 2. Themethod of claim 1, wherein the phantom comprises an aggregate phantomhaving a plurality of self-contained sections, the locating comprisesseparately transporting and re-assembling the sections within theimaging system, the attributing comprises attributing the virtualfeatures to regions in each section, and the processor compensates forany differences in composition between the sections of the aggregatephantom in determining the signal uniformity throughout the measurementvolume.
 3. The method of claim 2, wherein each virtual feature has aspherical shape.